In today’s modern era of the business conducted at the speed of light HR professionals, must of necessity take quality decisions. These decisions must be based on accurate verifiable data and will determine the way and manner in which talent is hired, managed and retained. The end result of this entire process is improved return on investment (ROI).
HR analytics is what makes this possible. It equips managers to harness the productivity of personnel to the maximum by creating a better work environment.
- History
- Definition
- Why it is Important
- Types
- Examples
- Strategy
- HR Metrics and Analytics
- Advantages
- HR Analytics vs People Analytics vs Workforce Analytics
- Challenges
- Technologies Enabling HR Analytics Software
- HR Metrics vs HR Analytics
- Best Companies
- Future of People Analytics
- FAQs
History and Revolution
The effect of the industrial revolution on humanity cannot be quantified. New methods for the specialization of tasks, the concentration of capital and centralization of workforces forever changed the socio-economic business outlook.
Frederick W. Taylor, who was a leading authority in human resources, crafted a methodology of scientific management built on four cardinal principles. These principles were the use of systematic techniques based on a scientific study of tasks; scientific selection, training, and development of personnel.
Detailed supervisory guidance of personnel for each individual task assigned along with performance feedback as well as the application of scientific management principles to labor force planning through the division of work which involved an even split of work between managers and staff under them.
The ultimate goal of all these processes was to improve worker conditions, and thus increase production based on a minute by minute analysis of production per task. This goes down on record as one of the first known cases in which HR analytics(1) was applied. After peace was restored in the wake of two destructive global conflicts (World War 1 & World War 2), organizations brought onboard HR personnel.
Management practices were interwoven with organizational behavior and social science. This led to the rise of personalities, who became leading authorities in HR analytics. A notable example was Jac Fitz End who wrote “How to Measure Human Resources Management” in 1984.
The growth indices of HR analytics fueled by the advent of the internet became widespread on a global scale. This led to the recognition of people analytics, as a critical factor in an organization’s success. In addition to these companies using HR, analytics had their processes enhanced by new technologies like artificial intelligence (AI), machine learning and visualization tools.
What is HR Analytics?
A simple HR analytics definition can be given thus: human resource analytics (HR analytics) is a specialized branch in the field of analytics that applies processes such as modeling and statistics, to the human capital within an organization in order to improve employee performance and retention, leading to favorable business outcomes and a better return on investment.
Importance of HR Analytics
HR analytics is primarily based on data. It enables HR practitioners to collate, organize and analyze HR data related functions such as recruiting, managing, engaging, and retaining top talent to aid better decision making in these areas.
Large volumes of data are created daily by HR departments using software tools and technology. The chief aim, however, is to interpret the data correctly and harness valuable insights gained from it. The importance of HR analytics can be enumerated below:
-
Improves HR performance:
HR performance can be improved by one major factor: better decision making. HR analytics is important because of the increased need for data which makes this possible.
-
Identify the best performing talent:
Critical insights can be gained from accessing and analyzing data collated with regard to a company’s workforce. A key example of this is the identification of the best performing personnel in an organization.
-
Identify attrition and its causes:
Employee data can reveal and expose departmental units suffering from maximum attrition, patterns of attrition, identify commonalities and isolate root causes.
-
Predict in-demand skills and positions within the organization:
HR analytics data can help you as a practitioner determine accurately skill and positional requirements within your organization.
-
Transforms the role of HR as a strategic partner:
HR analytics places the HR department in a unique position to influence personnel matters within an organization. This is because employee data grants valuable insight thus empowering human resources tremendously. HR can furnish the company executive with accurate, tested, verifiable data to back up policies undergirding staff recruitment, retention, and engagement.
What are the Benefits of HR Analytics?
Human resource analytics has been found to be a key determinant in moving a company from the level of mediocrity to one of prime excellence. What then are the tangible benefits of human resource analytics? These benefits can be enumerated below as:
- Personnel development giving rise to better labor force planning
- Better quality employee experience
- Process enhancement
- Technology-driven tasks
- Superior talent engagement
- Increased labor force effectiveness
- Diminished retention
Different Types of HR Analytics
It is clear beyond all reasonable doubt that talent is a major determinant of the success of an organization. The capacity of a business concern to attract, manage and harness resources is a long-term pointer to its success.
There are at least five types of HR analytics every manager must know:
-
Organizational Culture Analytics:
Culture refers to the collective unspoken norms governing conduct, principles, and patterns of human behavior that prevail in an organizational setting. Therefore, it is proper to say that organizational culture analytics is a process of judging and a better understanding of your workplace culture. An accurate understanding of this enables you to track noticeable changes. Consequently, you can detect early signs of the culture becoming unpleasant.
-
Capacity Analytics:
Capacity does impact revenue. Capacity analytics enables you to confirm how operationally efficient your workforce is. A company may specialize in the laundry of clothes, but analysis can reveal that the staff utilizes the bulk of their time on meetings rather than on the main task of laundry. This kind of behavioral analysis will help determine how much capacity each individual has to grow.
-
Employee Churn Analytics:
This involves a process of determining your labor force turnover rate. Analysis of data, which is futuristic in this regard, can help predict future trends and reduce staff attrition. Data collated from the past, called historical employee churn, state in detail the employee churn rate from the inception of employment. In order to properly determine employee churn analytics both predictive and historical churn data are important.
-
Leadership Analytics:
What leadership analytics does is to analyze the various facets of the effectiveness of workplace leadership. This covers the entire spectrum of strengths and deficiencies of an individual. It is essential that this assessment is carried out because poor leadership is virtually zero leadership and results in loss of revenue, loss of time and employee churn.
Consequently, the business will not attain its full potential and employee retention will be abysmally low. The data required for leadership analytics can be obtained from both quantitative and qualitative research. This involves the use of a combination of methods like polls, focus groups, surveys or demographic research.
-
Capability Analytics:
The degree of proficiency of personnel and their combined skill set pool will determine how successful a business is. Capability analytics covers the talent management process that helps you pinpoint the core competencies of your labor force. Once determined these can be set as a standard, compared to the capabilities of your staff and any gaps can be captured.
Best HR Analytics Examples
HR analytics starts with the collation and mapping of all relevant data. A typical HR analytics example is assessing the impact of employing talent based on an organizations’ financial performance.
Logical informed conclusions are then drawn based on statistical input data which are your organization’s financial performance data and employee engagement data. Recent employee engagement data can be readily obtained from employee engagement surveys conducted once every year.
Strategic work areas can then be closely examined based on the output of the data collated, which opens the door to limitless possibilities. This enables you as an HR analytics practitioner to make highly accurate futuristic predictions.
These predictions cover the spectrum of both performing and non-performing areas of your corporate entity. It is possible with the right data, to draw conclusions for budget allocation per employee training or even predict which of the new intakes will become the top performer in your company.
What is HR Analytics Metrics?
Hr analytics metrics are a form of measurement criteria that allows you to monitor key areas in HR data. Three of a few such areas, along with key HR metrics relating to them is as follows:
-
Process optimization:
It helps analyze what is done in human resource management. The focus here is on changes in HR efficiency and effectiveness over time. These vitals are then used to recreate what takes place in human resources.
-
HR operations:
– HR efficiency (time duration for resolution of HR self-service tickets)
– HR effectiveness (impression of the quality of HR service)
-
Organizational performance:
– Staff attrition statistics
– Absenteeism percentages and behavior
– Percentage of regretted loss
– Turnover percentages
Best Ways to Use HR Analytics Strategy in Human Resources
The human workforce is a company’s most valuable but also most costly asset as 40% – 80% of the total company budget goes on maintenance of staff. HR analytics can equip HR to better support their organization by maximizing their recruitment strategies while keeping hiring costs manageable but also simultaneously hiring top talent. A few of the best ways to use HR analytics strategy in human resources are:
-
Recommendation of Employee Incentives:
Incentives attract and retain top talent. Data gotten from analytics can help HR determine which incentives will be most effective.
-
Improved New Intake Training:
New hires frequently undergo training once engaged by a company. Valuable data can be collated from such training programs, the performance of the new staff in their first few months and survey responses from new personnel. Once all the sources are combined human resources can identify both effective and defective areas in the company’s training program. This data can then be used to not only improve the training but isolate areas where employees are lacking.
-
Top Talent Retention:
The most important metric is staff feedback. HR is the company’s first point of contact with regards to how they feel and what they need in order to achieve success. The use of predictive and prescriptive analytics software helps an organization easily and quickly sort massive amounts of data, gain useful insight about employee perspective then take proactive measures to meet the needs of and retain top talent.
Difference Between HR Analytics, People Analytics, Workforce Analytics
HR Analytics
This is the branch of analytics tasked exclusively with metrics of the HR function. It covers functions like training expense per staff, time duration until promotion and time to engage talent.
People Analytics
Technically, this has to do with analytics about people that is all-encompassing. It captures not just the employees of an organization but also customers of the organization.
Workforce Analytics
This arm of analytics specifically addresses employees of a business concern like remote employees, on-site staff, freelancers, consultants, gig workers, and all other personnel employed in various capacities. Here statistical methods and metrics are applied to the performance of workforce talent.
The key differences per the three terms are that HR analytics covers a broader scope of data while people analytics and workforce analytics has to do with data metrics exclusively related to people and their behavior.
What Are the Major Challenges of HR Analytics?
Implementing HR analytics can sometimes be a daunting task as organizations experience challenges in the process. What are the major challenges of HR analytics? These challenges are:
- Establishing a relationship between actions and insight to the return on investment (ROI)
- Data privacy and conformity
- Data cleansing
- Identification of a skilled pool of talent capable of data collection, management, and reporting
- Inability to identify the most important data as well as voluminous data parsing
- Data quality
- Achieving executive leadership buy-in per the importance of HR analytics
- Determining premium quality HR technologies for tracking data
How Technologies Help to Make HR Analytics Software Better
In the not too distant past, HR usually only managed administrative tasks and played a support role in business. However, in today’s business world, HR has undergone an evolution such that it is the most valuable asset to an organization. The following are ways how technology helps to make HR analytics software better:
- Payroll management
- Retirement
- Benefits Administration
- Time and Attendance Tracking
- Onboarding
- Recruitment
- Performance Management
- Talent Management
- Training & Development
The Future of HR Analytics
The future of HR analytics is virtually limitless in scope. Corporate bodies have realized that data-driven company culture is essential in order to retain both market share positioning and top talent. The benefits of data analysis as a critical tool must be sold to company executives so that vital human resource management solutions can fuel the drive to attain goals.
In addition to this, the role of psychology and specifically industrial-organizational psychology (IO) in HR analytics is becoming increasingly important, as it is directed towards enhancing productivity and personnel comfort. This is achieved by ensuring staff is engaged in jobs they are best suited for within the organization. HR analytics is extensively used by I-O professionals to ensure this is properly done.
There are ten disruptions that have been identified by Josh Bersin from Deloitte which will and already are defining the future of HR analytics. They can be enumerated below thus:
- Continuous performance management
- Acceleration of HRMS and HCM cloud solutions
- Recreation of learning opportunities for corporate staff
- Feedback, engagement and analytics tools
- Change to productivity from automation
- Innovation-driven recruiting market
- The explosion of the well-being market
- Growth and maturity of people analytics
- HR innovation
- Intelligent self-service tools
Difference Between HR Metrics and Analytics
Metrics at its core has to do with operational measures. It aids in the analysis of performance, efficiency and the impact of certain practices. Analytics on the flip side carries out a comparative analysis of variables in order to guide human resources in taking future decisions.
The difference between HR metrics and HR analytics is as follows:
| HR Metrics | HR Analytics |
|---|---|
| Metrics handles tangible data, which is easy to measure but is of low value. | Analytics, on the other hand, is mainly concerned with intangible data, which is hard to measure but is of high value. |
| Metrics give information. This puts the spotlight on monitoring and presenting historical data like website visitations, the volume of candidate applications, number, and types of recruitment campaigns undertaken yearly. | Analytics takes into consideration both past and present data, which helps to grant HR practitioners a great deal of insight, optimizations and enables them to forecast. |
| Metrics can furnish you with an insider perspective on a business due to the use of data from in-house sources. | Analytics gives an outside-in viewpoint due to the use of both external and internal sources. |
Which Companies Are Using Analytics in HR?
A common term trending in business circles today is ‘datafication”. This refers to using the power of “big data” to transform and drive human resource processes. This in effect is the datafication of HR. here are a few examples of companies which are using HR Analytics:
-
Google(Evaluating Hiring Processes)
Data from thousands of job interviews conducted, comparisons of interviewers’ evaluations of candidates alongside their eventual performance was analyzed by Google. The data helped the company determine the right number of job candidates to interview for each position as well as qualities that were a pointer to success at Google.
-
Shell(Identification of good idea-generators)
A database of ideas put forward by about 1,400 employees, over a number of years was analyzed. The original idea generators were asked to play some video games designed by neuroscientists whose aim was to test human potential. The game results were checked against the real-world results of the ideas proposed. Shell was thus able to identify people with a tendency to have the best ideas.
-
Xerox(Increasing employee retention)
Big data can unveil insights that are simple but effective. Xerox carried out extensive data analysis on its customer service employees. The results generated showed that the longest-serving employees were those who lived close to the company office and had access to transportation that was reliable.
Frequently Asked Questions:
The following are FAQs on HR analytics:
Q. Should HR Analytics Interest me?
A. Yes, it should. It is an area of emerging new focus. New products and methods of analysis on employee data have been developed, tested and put to use by HR system vendors.
Q. What is HR Predictive Analytics?
A. Predictive analytics are all around us. In short, it is a technology that collects existing data and analyzes critical findings to forecast future behavior. Predictions are, hence, based on solid data that is very specific and can be used to predict, with accuracy, success or failure in finances, business, and human resource efforts.
Conclusion
Human resource analytics continues to be widely accepted by human resource professionals and talent sources as a tool that can add value to the bottom line of any organization. With the right understanding and implementation, data that is quantifiable can now be used as an essential metric for long-term success in recruiting, retaining, and managing people.
Other Useful Resources:
4 HR Analytics Framework to use in Your Organization
5 HR Analytics Research Papers Every CHRO Should Read
Top 10 Human Resource Analytics Trends to Follow in 2020
